|
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Absolute deviation, 绝对离差
, C5 W( P. E/ ZAbsolute number, 绝对数
4 f2 T+ w) C0 w' c, W; N2 _6 fAbsolute residuals, 绝对残差
: \, u; C4 } @! s l+ I4 ZAcceleration array, 加速度立体阵1 @. y9 b) s/ ]$ Y
Acceleration in an arbitrary direction, 任意方向上的加速度3 c+ ]$ b. h& f1 k7 X9 T
Acceleration normal, 法向加速度
3 y0 t1 [) M+ u9 N. qAcceleration space dimension, 加速度空间的维数$ X/ ]$ q V. D9 p
Acceleration tangential, 切向加速度, ]; x. E7 B# u+ ]- P3 S" R
Acceleration vector, 加速度向量
3 v/ b4 h/ m- p7 O& ^4 _& G( eAcceptable hypothesis, 可接受假设
* U( \) E/ T- g h+ ?( `Accumulation, 累积
. N4 G2 a" x0 \6 `( n: m# i9 N' OAccuracy, 准确度
+ q, X' N, w' wActual frequency, 实际频数
" J2 R E9 R) w. ?Adaptive estimator, 自适应估计量
$ {7 m; D0 P9 {+ ? P+ J; h" {Addition, 相加8 @, ]: V& @6 U% o0 ]8 J
Addition theorem, 加法定理* M6 s+ d8 y) n' ?
Additivity, 可加性
6 n( r. p, k; O( c ^7 Y! h8 j+ VAdjusted rate, 调整率$ J& z- {. x3 O2 M
Adjusted value, 校正值
, k- a5 a* p& J- I/ TAdmissible error, 容许误差& c( P5 `, t5 a( a u
Aggregation, 聚集性$ f: Z( V* b" P; h& u" [
Alternative hypothesis, 备择假设
0 o# V: X4 Z- @: k# QAmong groups, 组间
4 V! X6 K" }( {$ h: q8 [0 C8 `Amounts, 总量
, \/ g& s# ~0 L1 k2 K4 a+ `Analysis of correlation, 相关分析
3 t$ w6 y* b, {$ X8 j7 fAnalysis of covariance, 协方差分析
9 X3 v1 y4 j% U* U$ X3 d/ [Analysis of regression, 回归分析) x6 ]6 l5 [6 ?
Analysis of time series, 时间序列分析
: v/ S7 }: L& TAnalysis of variance, 方差分析9 w4 J t Q& |% m6 M5 R" I+ ^
Angular transformation, 角转换
. ^ H* {3 D& bANOVA （analysis of variance）, 方差分析
, X( \" C' ^6 t# G$ Q _ANOVA Models, 方差分析模型
+ T9 a! e9 _( i3 A; V/ hArcing, 弧/弧旋- }; o7 ~+ t" p
Arcsine transformation, 反正弦变换: p3 \3 o1 }/ J l0 g4 n* P5 `
Area under the curve, 曲线面积" @+ l9 N. z. O) w) @" W
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 $ k8 k# a% K$ b
ARIMA, 季节和非季节性单变量模型的极大似然估计 ( b; I _ W; e: \% A5 Q+ R
Arithmetic grid paper, 算术格纸
$ Z( N9 s# D+ V% w1 R: @2 S& rArithmetic mean, 算术平均数) }0 E: V. l) ^) Z, }2 p
Arrhenius relation, 艾恩尼斯关系/ y) l. F: o" n: M. C: r
Assessing fit, 拟合的评估
) R p/ `8 t |5 F% g& o( hAssociative laws, 结合律
. b P+ @' R$ a6 z0 N: `1 }Asymmetric distribution, 非对称分布/ d& N) u1 x+ S3 z
Asymptotic bias, 渐近偏倚
2 O3 }1 y" G; P' g$ m. TAsymptotic efficiency, 渐近效率6 `( k$ O; x S1 H
Asymptotic variance, 渐近方差
7 w0 T- p; W' q4 R% f }6 Z* BAttributable risk, 归因危险度( O' q+ U V# P @! ~' r
Attribute data, 属性资料
" }( ]- a" c/ t& pAttribution, 属性
% I- F* ^$ H4 _Autocorrelation, 自相关$ [& h" j. W" I6 Y: ?8 _
Autocorrelation of residuals, 残差的自相关
4 T4 q( _! B/ k+ m5 B! l5 a4 CAverage, 平均数0 d, U# s. \* m; Z
Average confidence interval length, 平均置信区间长度" T7 Y' m% L5 s3 H7 }
Average growth rate, 平均增长率6 V8 L( e) y8 ]- N+ l
Bar chart, 条形图
& ]. J, U' Z x2 o0 b% KBar graph, 条形图
0 b; W4 ]4 p4 I- m& e8 XBase period, 基期
$ `: w" |7 c& R* c. G( ?& [; ] jBayes' theorem , Bayes定理
* g6 ~7 c7 o. Q8 X( @" YBell-shaped curve, 钟形曲线
4 P2 U( f! k+ Z8 PBernoulli distribution, 伯努力分布: H. Q7 N# v0 D) a8 j
Best-trim estimator, 最好切尾估计量
" E) L# I8 C. V a/ I: [Bias, 偏性
( P* Q8 s* y. E9 ~4 a5 E, P9 DBinary logistic regression, 二元逻辑斯蒂回归
- B2 f+ |; q5 E' IBinomial distribution, 二项分布" t1 M& s; c8 K6 j! Q3 e1 i
Bisquare, 双平方
- r, ^* P, Z K- Y; D2 ? ~Bivariate Correlate, 二变量相关. j& c" H* i2 |8 C# e) V1 U, R$ f
Bivariate normal distribution, 双变量正态分布
# L( }, ~/ i! A* h& Y7 F7 `" Z' VBivariate normal population, 双变量正态总体, y {: k: s& k
Biweight interval, 双权区间
+ U" d7 d- w! j4 `6 EBiweight M-estimator, 双权M估计量+ Q, K% K1 \. y8 F0 L
Block, 区组/配伍组9 @5 H; ?2 D% R7 t; S' B, S0 C
BMDP(Biomedical computer programs), BMDP统计软件包
9 |$ d1 e6 {1 RBoxplots, 箱线图/箱尾图5 _0 p5 C1 D3 g! x( _$ p# K. w9 ]0 \
Breakdown bound, 崩溃界/崩溃点
/ q4 h; a8 q" i4 cCanonical correlation, 典型相关, G* }. M. S+ u; o( j( P4 C$ T& [
Caption, 纵标目/ i. S8 [2 r) s$ z3 y
Case-control study, 病例对照研究
- _: h. O1 W2 h3 Q% r" n* _1 bCategorical variable, 分类变量7 k- g- w& F }5 c5 ]. i& B" l
Catenary, 悬链线
8 t, x6 C& j3 J$ t/ X) X1 nCauchy distribution, 柯西分布9 D; p! o5 [6 g" {$ n
Cause-and-effect relationship, 因果关系* ]$ p1 T% c/ P5 y9 P( n* P h; _) e
Cell, 单元
5 @* a- {1 c6 l6 lCensoring, 终检9 |( v8 n1 g# p: P1 z- A, Y% F. J# b
Center of symmetry, 对称中心/ Y% f+ s8 ?/ s3 q7 ~
Centering and scaling, 中心化和定标: B5 \1 k6 I& {; Z" q8 e# o
Central tendency, 集中趋势
; N8 F) H; a9 H0 T3 D. `Central value, 中心值, C; Y% s* q4 U8 I. G6 o9 z
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
& _4 O" S4 @3 g) `: B/ ?+ gChance, 机遇
* U8 w" {. ` q" M* mChance error, 随机误差
" }" ~5 n* k; hChance variable, 随机变量. u8 j2 e8 e# [6 {' p
Characteristic equation, 特征方程& Y$ L% S- H L& h. |
Characteristic root, 特征根
- j* \7 ]' o }4 t9 D6 W* O2 jCharacteristic vector, 特征向量
4 q: ^5 k# q' z, p3 YChebshev criterion of fit, 拟合的切比雪夫准则$ Q* ^$ f5 a, l+ q0 U$ t v
Chernoff faces, 切尔诺夫脸谱图
! p6 _) v. M, K2 e! m1 q wChi-square test, 卡方检验/χ2检验6 _+ Y3 q8 o. f
Choleskey decomposition, 乔洛斯基分解0 b3 W" R, Z/ v+ K% d" Z$ T7 T
Circle chart, 圆图
: N: V6 o+ ~! f0 b5 t/ zClass interval, 组距
& {1 Y8 }1 z- V2 {/ }Class mid-value, 组中值" q8 K( y, l( ?0 p: u% g) A
Class upper limit, 组上限# ]+ _3 o9 E; c6 X
Classified variable, 分类变量7 `4 B+ D2 J5 c4 e, y
Cluster analysis, 聚类分析& i, c, i. M, e
Cluster sampling, 整群抽样( ~6 q8 \" }0 J2 O7 k! _" t7 K
Code, 代码
6 A$ N( i9 [' YCoded data, 编码数据
0 M- F3 x4 s$ ]& zCoding, 编码; P4 M+ r8 z, ^9 V# u. X
Coefficient of contingency, 列联系数
: W; U/ L$ t. c" ~* u. ACoefficient of determination, 决定系数% G6 x5 |: ? \; G" p
Coefficient of multiple correlation, 多重相关系数9 x8 F" i3 P# E# d. W A0 j
Coefficient of partial correlation, 偏相关系数
3 P. d* x9 h' V8 XCoefficient of production-moment correlation, 积差相关系数2 l' b. x) q' e7 ?* l
Coefficient of rank correlation, 等级相关系数
# Q* h0 \" i! E! P8 @Coefficient of regression, 回归系数8 y$ ?9 b( I- x3 p" P h0 ~
Coefficient of skewness, 偏度系数) Z! R8 S# T h# `9 Q" m
Coefficient of variation, 变异系数9 y5 i2 Q5 X1 Q5 W# v6 w* y
Cohort study, 队列研究( I. c/ f1 F5 l% V& ^9 J
Column, 列
- Q3 E: y# k3 P2 O0 d" hColumn effect, 列效应
# F/ ~ G4 C8 C+ mColumn factor, 列因素6 r: o1 S& P" J7 t) b( x
Combination pool, 合并' z) N e7 s- r% b9 J% k6 @. W3 ]
Combinative table, 组合表6 p& V+ b; k% b5 C' Y: g
Common factor, 共性因子
: e9 J+ d& I0 T% s/ @Common regression coefficient, 公共回归系数
) j( J7 U, O) m' J4 W8 DCommon value, 共同值
! N- M0 ^( Z M, q4 SCommon variance, 公共方差9 K& H6 }7 H0 y, @
Common variation, 公共变异+ d" H9 r9 U7 f! T- {+ }1 c8 b0 T
Communality variance, 共性方差" ?% p4 |* k3 s# D
Comparability, 可比性
( h0 a5 }& L/ F5 m6 i, lComparison of bathes, 批比较' }8 q2 i' b k5 @
Comparison value, 比较值3 ?! N) n( S2 w
Compartment model, 分部模型, m3 l% m0 ?# Y/ k) y; v" c
Compassion, 伸缩& ]3 z9 C2 _5 Z+ Q/ I
Complement of an event, 补事件
: J: G( P+ |1 r) ?8 M: cComplete association, 完全正相关
3 Y2 S# d1 c0 x2 N4 uComplete dissociation, 完全不相关
( P: l, h) t' PComplete statistics, 完备统计量7 V, v2 R( M3 F6 o7 c" r
Completely randomized design, 完全随机化设计2 p( a, C" v& v. I! K$ A4 R
Composite event, 联合事件
- V* Q% ?% b% d( K' u# jComposite events, 复合事件
9 s* Y# j* v& B, r3 DConcavity, 凹性
% w* U' k- d/ X# D0 OConditional expectation, 条件期望3 z% G0 ~9 m! T( o' \+ }& O, o! v7 }! E
Conditional likelihood, 条件似然1 L; D( D3 O$ d% h6 T6 ]. f8 q
Conditional probability, 条件概率( _& v$ K* m. v U" Y3 o
Conditionally linear, 依条件线性
7 b4 H$ O' q9 {6 \( m! ZConfidence interval, 置信区间2 m" x: c+ S% b6 e% ] n4 P
Confidence limit, 置信限$ v- l M0 m' g+ f9 R& r
Confidence lower limit, 置信下限
$ K1 q7 m0 ]+ J3 a @) ~Confidence upper limit, 置信上限
. q! R+ M: j5 ?Confirmatory Factor Analysis , 验证性因子分析2 e2 U+ X& [! s7 P, F
Confirmatory research, 证实性实验研究
" V7 {/ K1 {7 R' ]! HConfounding factor, 混杂因素+ |2 z5 ?2 Q0 [
Conjoint, 联合分析
x4 v+ n# R! [5 VConsistency, 相合性 p2 ]# e1 ~6 D! K) e. T
Consistency check, 一致性检验1 [! T8 _, q( [8 _
Consistent asymptotically normal estimate, 相合渐近正态估计
+ S: ]/ \. A' X! ^: v, KConsistent estimate, 相合估计) K! n1 u5 `5 P% \2 v* n) C2 h! F
Constrained nonlinear regression, 受约束非线性回归& |1 S- R7 l2 m3 u- Y- V" |: p
Constraint, 约束8 F; V- N+ F4 E& m7 e
Contaminated distribution, 污染分布
7 V6 I; V% l. z! b# {1 zContaminated Gausssian, 污染高斯分布
( a" k. P/ [ x& ^Contaminated normal distribution, 污染正态分布0 l3 I; @ g, D2 Y0 N
Contamination, 污染
2 D& F. j2 }0 d r. QContamination model, 污染模型( w3 t* P5 `: S2 S( G& M( S
Contingency table, 列联表7 h! [. P6 ^7 i+ }; ]6 F- T2 a/ c" [
Contour, 边界线
/ w- k5 C$ _$ ]5 F# o$ x0 {- lContribution rate, 贡献率1 N Y0 S% F+ R! ?' y# S2 T7 }
Control, 对照
: ^" A- s' Z# Y( d1 ~5 |- G0 UControlled experiments, 对照实验! v% M. y. m. I* }
Conventional depth, 常规深度
# ?+ B! ]; O: w5 pConvolution, 卷积
. K. W! c6 E8 p3 qCorrected factor, 校正因子( _, p" N$ k- C2 j& n
Corrected mean, 校正均值! y5 t# [9 [, F- g" f
Correction coefficient, 校正系数# o) L$ }& U& I" E$ r$ G: R
Correctness, 正确性
& Y8 P. t, o+ `" d3 n+ ICorrelation coefficient, 相关系数
6 C2 {4 }1 p6 F+ X! WCorrelation index, 相关指数4 [) S F7 j, k2 j" l. ^7 `
Correspondence, 对应
, C/ W' ? g0 \) fCounting, 计数
% L7 A; ~3 c9 X- H( `Counts, 计数/频数 ~$ W1 `* a9 P
Covariance, 协方差
! x& N7 N7 G _, qCovariant, 共变
" S$ \: A0 O3 v$ P. W9 dCox Regression, Cox回归4 B9 u, [6 Z, o9 S4 ?/ ]. F
Criteria for fitting, 拟合准则: h" f M# L, [5 A
Criteria of least squares, 最小二乘准则$ _3 ~8 M- f6 N: u/ H$ u$ [/ u
Critical ratio, 临界比
" A3 Q' v( J: u1 w. Y( iCritical region, 拒绝域! g! @( s- k; A4 }; I! m
Critical value, 临界值
1 e. e- n, o2 B1 r. kCross-over design, 交叉设计! n! g% R7 e8 V3 G
Cross-section analysis, 横断面分析/ y" D9 b \& C2 C% k
Cross-section survey, 横断面调查9 i8 O: E7 ?; ~5 I' _) ^; O
Crosstabs , 交叉表 / o' q* I Q' T7 Y3 O C
Cross-tabulation table, 复合表
7 E R4 w' g1 M$ { K7 NCube root, 立方根* e- l- @ S1 w0 w
Cumulative distribution function, 分布函数 j, ^9 G6 _% I0 Z
Cumulative probability, 累计概率
6 h% ?; A3 X, y0 L' iCurvature, 曲率/弯曲
& O1 G; C2 ~7 `" oCurvature, 曲率
5 a5 u' R( O7 qCurve fit , 曲线拟和 ! {$ e* b1 n8 m3 [6 W, w I: |
Curve fitting, 曲线拟合5 I; l- E/ |" h7 F; j3 c4 W$ f
Curvilinear regression, 曲线回归
- M$ M# }9 C* n* j* JCurvilinear relation, 曲线关系3 S. [3 S; d H/ M0 U
Cut-and-try method, 尝试法# z/ s" G( W. W7 N. y- `
Cycle, 周期: P# \7 u0 @( L" V$ N
Cyclist, 周期性8 |8 k4 r* ]# J4 r! Q" C( O
D test, D检验
$ b& @* X( r$ ~- T3 w$ c; a1 KData acquisition, 资料收集! q! c3 c3 V5 u# D
Data bank, 数据库 Y# I7 t+ k. I8 L
Data capacity, 数据容量
/ g$ i# q% H: Q9 u- |Data deficiencies, 数据缺乏
$ ]% x& m8 z6 ~$ Z& A4 MData handling, 数据处理, _* H1 a5 a5 g: F
Data manipulation, 数据处理
- U. H% O. k/ A( z3 FData processing, 数据处理
# A; w" X* o* J9 aData reduction, 数据缩减
3 L' Z! l% E9 j0 H* z; SData set, 数据集& i+ F$ W1 m L) {
Data sources, 数据来源
- g* w2 P8 Z M3 `5 Z" ]1 zData transformation, 数据变换
/ D" k3 V# H& RData validity, 数据有效性7 G G3 m i- e6 X) ~
Data-in, 数据输入
! Y3 g4 O* {7 N" @* h/ ~8 ^% WData-out, 数据输出
4 I% b {! c% g5 N, bDead time, 停滞期8 b0 Z3 f* b7 H! S$ Q( W' Q2 p" s
Degree of freedom, 自由度
# F2 F4 a. O5 q5 T- _% _Degree of precision, 精密度
2 V; J. ]+ Y. I: @# @Degree of reliability, 可靠性程度
) v) [2 k4 ?+ m+ lDegression, 递减
3 _' k2 n( [8 kDensity function, 密度函数
- e [: H+ O$ z7 h, WDensity of data points, 数据点的密度( A- v6 \' w9 t6 a& ^4 J Z# A
Dependent variable, 应变量/依变量/因变量! l) G' \+ a- t) B4 a
Dependent variable, 因变量0 W- d( ?" x4 c
Depth, 深度
& O% D K/ Y/ }, |# n( VDerivative matrix, 导数矩阵2 `- `$ Y, H# y) n$ j) d7 p9 v
Derivative-free methods, 无导数方法 w% U# c% p4 A* d8 j3 |! h4 d
Design, 设计
0 k5 {( j8 m, O3 gDeterminacy, 确定性
' u3 `+ H- h% [Determinant, 行列式
! o4 g+ x T8 E/ x! }Determinant, 决定因素2 J; h+ u1 \) `7 r( m
Deviation, 离差
) n' P6 j1 i% BDeviation from average, 离均差) @. _* O: e# a$ _
Diagnostic plot, 诊断图
; g/ W" ~0 p* Z$ WDichotomous variable, 二分变量$ `$ i# G( Q b( y
Differential equation, 微分方程* w/ F% ^; u; K6 A" E3 X
Direct standardization, 直接标准化法) j! X7 `( l7 o# y' g, ?2 ]8 v
Discrete variable, 离散型变量+ K1 N G/ z; M! R
DISCRIMINANT, 判断
& Z; d& |1 u) ^( a3 U3 LDiscriminant analysis, 判别分析6 \% m' I- j0 S4 e
Discriminant coefficient, 判别系数: ]4 D% {/ d! `$ _) Q/ R
Discriminant function, 判别值
( V' i" C( l( o2 B7 h# nDispersion, 散布/分散度
# n3 k8 J3 H) q: x* r1 VDisproportional, 不成比例的
8 n* Q# }0 g% r- ~3 D+ WDisproportionate sub-class numbers, 不成比例次级组含量
1 _ E: \9 v0 f: j/ f5 y hDistribution free, 分布无关性/免分布
% ~2 v) R6 h* U3 N5 H6 Y, ]Distribution shape, 分布形状
) R2 M' |+ M1 Z. t& S9 VDistribution-free method, 任意分布法
! g& {, V' Y: b E5 e$ hDistributive laws, 分配律! B, ?9 H: ?" C$ e4 e+ @
Disturbance, 随机扰动项
, s( P# i+ }/ P6 n/ Z! XDose response curve, 剂量反应曲线" E4 c0 ?0 d/ A' A
Double blind method, 双盲法' a# \# Q0 Y! I& @
Double blind trial, 双盲试验
$ s0 |: S+ y- q+ [+ ZDouble exponential distribution, 双指数分布8 G4 ?5 m5 |/ F5 @ ?$ F9 k
Double logarithmic, 双对数
, N9 f3 `! h( ^* U: E: p1 f3 cDownward rank, 降秩
7 U" h( S8 Q$ e; d% X; @9 c7 xDual-space plot, 对偶空间图* M9 M0 v7 b# V; c1 d
DUD, 无导数方法/ z' {9 O( {- B0 Z4 i2 @4 |6 n
Duncan's new multiple range method, 新复极差法/Duncan新法
8 J, D$ P9 `2 t: hEffect, 实验效应
$ t1 d: L( P% {1 z+ e7 PEigenvalue, 特征值; B, A( p+ u1 [% S7 s/ u9 b' q% s
Eigenvector, 特征向量& d4 a2 Y4 [, o8 O, H
Ellipse, 椭圆$ K9 j) G- t0 x5 M/ S0 \ A/ Y! V
Empirical distribution, 经验分布
5 K/ V& ], ~/ w" V8 L/ B JEmpirical probability, 经验概率单位
# x! Z3 Q( L* @9 I4 f: f) C4 R1 OEnumeration data, 计数资料
0 F3 M- K# t: C; hEqual sun-class number, 相等次级组含量
% ?7 t& o: `- FEqually likely, 等可能
. H/ j# i1 g" w5 M: v0 A2 Z3 c4 iEquivariance, 同变性; z, p |% @6 I. h3 m U- T
Error, 误差/错误 I, q6 H: Y, W7 Q: _
Error of estimate, 估计误差
! I% m* d4 [* t8 XError type I, 第一类错误
; y9 H* y" w& ?, ]5 J" n ZError type II, 第二类错误$ c/ K! _5 ~ q
Estimand, 被估量 `7 |7 N- A: n3 t/ x. d
Estimated error mean squares, 估计误差均方
" f# u% S6 {) n+ ?Estimated error sum of squares, 估计误差平方和3 x6 S# a4 s- K8 S6 f/ {
Euclidean distance, 欧式距离
/ q9 r( k2 j) S6 G- WEvent, 事件
' t# s5 Y" n0 u' L$ e6 pEvent, 事件) i% _/ S( _1 Z8 s- N( { b
Exceptional data point, 异常数据点
8 m7 C2 N' T/ Y9 V; B+ zExpectation plane, 期望平面
& ~, P2 R3 M% k; r9 iExpectation surface, 期望曲面
' v ]/ n" |) z' bExpected values, 期望值
- Q8 D. y- w) h; Z+ b2 N1 EExperiment, 实验7 c' [* X, W& @! t
Experimental sampling, 试验抽样
5 `; [6 i' D' kExperimental unit, 试验单位. w) f$ i0 Z+ `& b/ k* J
Explanatory variable, 说明变量4 q8 A/ E* H2 s1 i& V. p. |& I. ^
Exploratory data analysis, 探索性数据分析2 p. G( N8 C$ w8 b2 i
Explore Summarize, 探索-摘要7 T; Y/ J! a) D2 k
Exponential curve, 指数曲线 k/ [7 z4 @% e$ \
Exponential growth, 指数式增长
+ e8 o5 _# E- LEXSMOOTH, 指数平滑方法 ' B' r4 R+ [$ a" y! C) c+ M _4 {' h
Extended fit, 扩充拟合
( n. U% Y4 M) K" h. _* BExtra parameter, 附加参数
8 Q3 t& j2 I8 S& `; g; x0 JExtrapolation, 外推法4 ?, \1 l- K1 g; N" Y& Q* t. q
Extreme observation, 末端观测值
" z: T7 l- o1 w7 }9 ^% M7 bExtremes, 极端值/极值' P" ~- C8 N# C: q) J
F distribution, F分布
* R7 L# ^) b- j9 ?- Y, yF test, F检验
& }* X9 ~9 w! ^Factor, 因素/因子
4 e, e* R" \0 j8 RFactor analysis, 因子分析
, K( |4 l! H) z- A& nFactor Analysis, 因子分析
: ~7 U! V0 {: B. C8 p& wFactor score, 因子得分 - y1 W! a A+ D, J
Factorial, 阶乘
- o. G! b1 y7 L8 QFactorial design, 析因试验设计6 t! N" ]! D, C9 E* z
False negative, 假阴性
; ~4 u. \, x$ F; `& w4 f8 @ oFalse negative error, 假阴性错误! i4 U' v+ v( F& U& _: {( V
Family of distributions, 分布族; y: p3 Z: c6 J* I1 u7 p( [! r, i( F% ~
Family of estimators, 估计量族
( B+ f& x& Q8 a; Y6 RFanning, 扇面
+ g! J/ }" g* `Fatality rate, 病死率8 x5 h1 ?$ c' U6 c* y! f
Field investigation, 现场调查
' z' z4 G* T! e, @4 m K8 r. A, gField survey, 现场调查
' G8 |3 l2 c/ U% U% i9 GFinite population, 有限总体
) j0 k A C: vFinite-sample, 有限样本+ J: I1 Q1 k' a6 j' i- P
First derivative, 一阶导数
K: V8 P0 b& G7 NFirst principal component, 第一主成分! X& O$ M" Y& Q6 R9 z
First quartile, 第一四分位数2 e8 K1 B. w! W
Fisher information, 费雪信息量" U# {1 L5 _0 F* |/ t1 ]
Fitted value, 拟合值: C; j. d5 L) v% H
Fitting a curve, 曲线拟合. ]: N1 D Z2 l2 l; L) f$ {! J
Fixed base, 定基1 c; C& w$ G3 B1 }2 R, p, `
Fluctuation, 随机起伏- R$ L( I0 {5 Q( {3 e* M% X$ [
Forecast, 预测
: E; ^' ?* q4 CFour fold table, 四格表
/ k1 Y) \( W& n6 U& N. fFourth, 四分点) s8 b' b) k E' [
Fraction blow, 左侧比率- K% E. W1 @: z- B v7 e7 \: Q
Fractional error, 相对误差
7 W3 E& U8 o0 q9 YFrequency, 频率
4 q$ B% ~( J* c5 vFrequency polygon, 频数多边图
2 j" d) y( [8 F' PFrontier point, 界限点
9 T* ]' F7 Q3 E. d5 aFunction relationship, 泛函关系( x6 e5 ~7 W# c0 ]& c' O9 g
Gamma distribution, 伽玛分布
- L6 T/ [ q1 ~( mGauss increment, 高斯增量
- U; a! V/ q2 v; k: E0 `8 }, ZGaussian distribution, 高斯分布/正态分布
3 j, z# x w. U1 J- Y: VGauss-Newton increment, 高斯-牛顿增量5 n7 n; }" A8 R" Q& u
General census, 全面普查
9 [$ ?' K# c2 N M9 w3 o, \GENLOG (Generalized liner models), 广义线性模型
+ {$ F* Q$ e1 Y4 H3 x/ f6 }4 EGeometric mean, 几何平均数# a( [0 b4 {: [( ]5 w) i; j9 g
Gini's mean difference, 基尼均差
0 `9 ~. H/ x! }2 d$ {3 j$ NGLM (General liner models), 一般线性模型 j; n- I- X0 }$ e- W4 K
Goodness of fit, 拟和优度/配合度" m" C/ W" f0 q& A( s; S
Gradient of determinant, 行列式的梯度
! x, W0 {- A6 }: v" q. uGraeco-Latin square, 希腊拉丁方
5 j& u- H8 Q, ^8 A" pGrand mean, 总均值9 B9 g9 ?4 {2 s7 V7 _; g8 O
Gross errors, 重大错误5 U" J d- R0 h" k/ T# w2 T2 ^
Gross-error sensitivity, 大错敏感度
. F7 p: M+ j* V0 t" M7 ZGroup averages, 分组平均& a6 d8 N2 |, v5 H8 K8 h
Grouped data, 分组资料 h3 h+ I. ^" ^' R k# Y5 c
Guessed mean, 假定平均数
- S# A) f- a" A- H4 B' WHalf-life, 半衰期
7 R# C& @' K3 J: N" EHampel M-estimators, 汉佩尔M估计量( a0 i$ P- {3 O% c
Happenstance, 偶然事件
6 n/ f. s; }+ E! I' M( A- c* W% GHarmonic mean, 调和均数8 T$ X) S5 f8 `7 ]: H) }& }
Hazard function, 风险均数
3 m. U: q" t: \+ Z3 Z2 yHazard rate, 风险率
. {# y; W. Z+ ~0 O* tHeading, 标目 0 U3 Y% X, i" A4 E
Heavy-tailed distribution, 重尾分布) A, \0 l+ O2 V/ ~+ [& J# r
Hessian array, 海森立体阵
2 v: K" X+ w1 w m2 XHeterogeneity, 不同质
* H5 j" q3 V" A4 ]Heterogeneity of variance, 方差不齐
9 P9 O- ]1 u& v( T* }Hierarchical classification, 组内分组. y3 p- X1 g6 v4 i) S8 @4 Z3 o7 D
Hierarchical clustering method, 系统聚类法7 J. R1 Z7 y. z9 f
High-leverage point, 高杠杆率点
7 B) z/ [' b7 w0 \' d. N% \HILOGLINEAR, 多维列联表的层次对数线性模型" M$ h$ g: O. x
Hinge, 折叶点' a/ Z. q% H! D/ d( J
Histogram, 直方图& ]. V; ^! u3 \# ?5 d
Historical cohort study, 历史性队列研究 & Y8 Q) t5 C$ K5 y- W
Holes, 空洞
# ^4 w2 M0 a& h5 hHOMALS, 多重响应分析- @6 r$ b I: g4 ~
Homogeneity of variance, 方差齐性
% c. h+ a! Q" J6 LHomogeneity test, 齐性检验0 U" G+ K( ?/ c* H- L% h4 b7 y
Huber M-estimators, 休伯M估计量" o0 Y4 j+ K7 W6 B) Y
Hyperbola, 双曲线 L3 h( n! ~ K9 g w5 A1 U
Hypothesis testing, 假设检验& I1 V! j4 u f
Hypothetical universe, 假设总体
+ H% l1 `+ r8 C |Impossible event, 不可能事件5 R, G C5 C7 j; f& r1 h% U( v
Independence, 独立性
% _3 p; p% z+ N6 ]) mIndependent variable, 自变量
/ {& A* B& N, M1 X* CIndex, 指标/指数& }, E$ R" E6 W$ c9 y
Indirect standardization, 间接标准化法
2 L! Q, a7 Q! ^) |7 m: n) z/ VIndividual, 个体
) f- |, E- p1 q# ~& e$ gInference band, 推断带
/ a6 u, [3 ^/ S: \Infinite population, 无限总体3 ]% f- x, x( L) E
Infinitely great, 无穷大% C7 n0 |, U/ b7 X4 \) x
Infinitely small, 无穷小
' B. {2 [: o3 yInfluence curve, 影响曲线
- @( f( j" ~- ?7 |) j2 r5 r) C0 `Information capacity, 信息容量* |/ V9 P: \+ f
Initial condition, 初始条件
( ?& R5 y3 y, w. M+ t) `Initial estimate, 初始估计值
& G. A8 L# G+ W$ zInitial level, 最初水平2 D% O8 _; a6 C5 E
Interaction, 交互作用# S; r' t J/ Q/ E: T K1 {" `
Interaction terms, 交互作用项/ ~' w8 Q$ d2 n1 {1 x/ A, g; B G& K
Intercept, 截距( B8 b1 D3 f; f7 x1 h0 c( b
Interpolation, 内插法
: w: j$ r: J% JInterquartile range, 四分位距
* |' m: d/ t6 l3 lInterval estimation, 区间估计5 O8 u# U3 {- p1 \" y& Y) t5 Z
Intervals of equal probability, 等概率区间
" O, ]$ I. t% S8 K6 kIntrinsic curvature, 固有曲率5 t' p/ K ?- p y, a" J
Invariance, 不变性6 B6 G( J/ r- z# `2 q) O: @! w
Inverse matrix, 逆矩阵
. q8 e& A5 I+ X! v: XInverse probability, 逆概率* r3 e: b6 ]; `$ C5 q
Inverse sine transformation, 反正弦变换1 I; r3 \4 Y# }: ]7 W; F! k
Iteration, 迭代 + P' i: ?- T5 y5 r% @
Jacobian determinant, 雅可比行列式
, f6 ~4 q; |+ n: n% E _/ rJoint distribution function, 分布函数
9 `8 H8 C. ?& F1 m. I( WJoint probability, 联合概率" A8 b" x- J O! `1 \
Joint probability distribution, 联合概率分布: L; _, x5 R0 o2 i3 ^
K means method, 逐步聚类法4 |* n) q( r1 ]5 V# C" `2 Q
Kaplan-Meier, 评估事件的时间长度
) A( w: T0 j" ]; ]- |+ {% YKaplan-Merier chart, Kaplan-Merier图
5 Q/ ?" r: T, t! |3 [Kendall's rank correlation, Kendall等级相关
) S! V+ q2 q _ x C: `3 DKinetic, 动力学
+ h& ~( X- d" {( U7 j3 g9 T6 MKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验" y4 Z a% Z/ X
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
& u3 P6 Q: U8 |) ]/ OKurtosis, 峰度
$ C& L& M3 Q# _Lack of fit, 失拟
6 U. W* z! s6 j8 \$ U4 vLadder of powers, 幂阶梯
# b/ ]8 P5 u+ t% p, e: bLag, 滞后# n# V! ]! D7 v; F5 ^4 i0 c
Large sample, 大样本
& m7 ~! Z6 u/ l% o, FLarge sample test, 大样本检验
: d: x; S/ t9 {/ ?* JLatin square, 拉丁方
3 F0 q" ]6 a( ?2 l6 jLatin square design, 拉丁方设计
* _+ }0 x' c4 `) Z1 LLeakage, 泄漏
# O3 F: T# a3 [1 c/ WLeast favorable configuration, 最不利构形
$ M% n" }) S' n$ U; ]- R" @: ~Least favorable distribution, 最不利分布2 J+ z+ z' N$ S% f# x b* {
Least significant difference, 最小显著差法
* p" A: ? y# [: j7 I' \0 sLeast square method, 最小二乘法. [2 m- m' z; D" N4 T- e9 N
Least-absolute-residuals estimates, 最小绝对残差估计
% G' M* I8 K& [; r& i' O, K" _Least-absolute-residuals fit, 最小绝对残差拟合
9 c2 m" z P' ]8 {% H. ~/ iLeast-absolute-residuals line, 最小绝对残差线
$ X K0 F3 I' LLegend, 图例
+ L* z) [) {5 H+ ~- G4 AL-estimator, L估计量2 h0 A; l# Y( M
L-estimator of location, 位置L估计量( W6 Q; g3 q# A o9 Q
L-estimator of scale, 尺度L估计量
8 w. q* {) d9 I6 A) C! z8 DLevel, 水平
: w. s& ?. s# a& |6 ?+ ?3 ?Life expectance, 预期期望寿命2 ^% @! O9 z- o6 M, O" D' L! g
Life table, 寿命表" a( b( B( |1 t& X I
Life table method, 生命表法
! |" }+ p: t+ |! r% rLight-tailed distribution, 轻尾分布8 c& G2 A0 Z [4 l% e3 |# t* c
Likelihood function, 似然函数
7 \$ V+ `! \. w) Q* \Likelihood ratio, 似然比. m1 ^; R9 R) G$ r2 N
line graph, 线图( w# j% U: K% Y& F% y
Linear correlation, 直线相关2 W5 n+ o& a+ h0 p
Linear equation, 线性方程
; [: q" [4 R: m3 Z8 J+ \" h9 VLinear programming, 线性规划- [$ ^, p' J/ E: I" n! r
Linear regression, 直线回归2 `& p1 I! I( {' Q6 k
Linear Regression, 线性回归+ v1 C1 u; _0 C, r8 P: G9 l
Linear trend, 线性趋势5 G3 u9 M6 ?4 N1 K# ?8 M6 m. ?
Loading, 载荷 . F, j; w# D% v! D; K; R$ k5 b: A
Location and scale equivariance, 位置尺度同变性6 h; |3 B7 o9 T
Location equivariance, 位置同变性! @$ p5 @6 G! |. o4 M
Location invariance, 位置不变性
! r- E$ Z6 Q6 G9 U& u6 LLocation scale family, 位置尺度族7 m. P2 m: y E& B h' n
Log rank test, 时序检验
& J- ^: A2 f. x3 S: X7 o* ]Logarithmic curve, 对数曲线4 M. h8 M8 x" p+ X8 B9 V+ u
Logarithmic normal distribution, 对数正态分布
$ y5 j; _# @# E# l A7 h& J# ZLogarithmic scale, 对数尺度
1 k/ y1 S. m3 p/ RLogarithmic transformation, 对数变换) X" A" s! @1 [* a/ X, z, M
Logic check, 逻辑检查! c/ I+ E( u* D4 {: w% v5 b
Logistic distribution, 逻辑斯特分布
' I3 E0 Z) @+ m5 O* V8 z/ KLogit transformation, Logit转换
6 K9 e' \5 T/ f% Q' ALOGLINEAR, 多维列联表通用模型
- c0 H5 u7 h, s0 F3 P" D" U( CLognormal distribution, 对数正态分布/ n9 V. S6 j6 }( C6 c; x( n
Lost function, 损失函数! a' h& _$ M) d% B, Y3 {
Low correlation, 低度相关* M* i2 J3 Q) I5 l; S
Lower limit, 下限" M! V5 F6 v5 n. t" q& @2 B+ g# U" ~
Lowest-attained variance, 最小可达方差8 k9 K5 b0 D% K/ Z; S# \
LSD, 最小显著差法的简称
9 d; y4 S4 m0 P& z$ E' vLurking variable, 潜在变量+ ]' D# O, ? @8 A0 C
Main effect, 主效应
6 a* ~) b Y' p, m& ~Major heading, 主辞标目' p1 {3 E6 K4 S; o6 \1 N
Marginal density function, 边缘密度函数
7 f- `3 Q% Q: r+ Q" BMarginal probability, 边缘概率
% b( u) H+ q3 q" p5 G" [. rMarginal probability distribution, 边缘概率分布3 {/ U8 S: [- g5 D3 X0 d
Matched data, 配对资料9 E( J0 c9 s! P! `
Matched distribution, 匹配过分布
, l: a+ a9 x$ ZMatching of distribution, 分布的匹配5 r6 b1 ^: ^ b D6 J9 b
Matching of transformation, 变换的匹配1 o% ^8 L& D' O# ~2 P! j
Mathematical expectation, 数学期望
8 |3 u8 q! v4 y$ I5 H6 `) x1 YMathematical model, 数学模型
$ @4 z5 p$ E# G, S4 LMaximum L-estimator, 极大极小L 估计量1 A2 T( \; Q* `) e( A" s9 M
Maximum likelihood method, 最大似然法
3 }; d' h* a% U/ D7 s2 CMean, 均数
) u4 z2 _$ Q* b1 xMean squares between groups, 组间均方' E) O# D( R1 t P O
Mean squares within group, 组内均方
0 h) w# r. o$ T3 o9 G! _! C$ \Means (Compare means), 均值-均值比较
3 U1 U, V/ L/ J7 }6 ?Median, 中位数
3 f5 h; u- {, O) zMedian effective dose, 半数效量+ r) a+ |; X c; T
Median lethal dose, 半数致死量1 ^2 ^4 [) J/ J/ Z6 ` K1 s, P
Median polish, 中位数平滑0 n4 R) t' j5 N. F& h% ]
Median test, 中位数检验, ^1 ~7 I# c$ e5 }- I5 Y7 Y
Minimal sufficient statistic, 最小充分统计量
0 f$ @& _: G, Z8 uMinimum distance estimation, 最小距离估计0 C" Y/ R ^# q) h+ Y7 i
Minimum effective dose, 最小有效量' s \% a5 ^) g) [
Minimum lethal dose, 最小致死量. s- U3 ^2 p k7 F1 ~& C4 h {
Minimum variance estimator, 最小方差估计量; G& W) W; V+ H1 S# T9 Q# e# w
MINITAB, 统计软件包- w+ k( \' l- t( n, c
Minor heading, 宾词标目
( z" `" B% w" tMissing data, 缺失值
+ g( \: `' o# F' w' ~Model specification, 模型的确定
- @0 `' ~) N! Z' h5 U$ _9 TModeling Statistics , 模型统计
9 @2 c# Q% Q* ?2 W: o7 `% N, ?Models for outliers, 离群值模型
: H! j9 O6 A; M& I" W: v3 oModifying the model, 模型的修正* F3 N& {1 n8 S2 B( @
Modulus of continuity, 连续性模
3 ~3 E0 u7 {, b5 r. K) BMorbidity, 发病率
$ ?' A6 L$ q. lMost favorable configuration, 最有利构形 X( r; `& o! Y. J/ a! a9 ~
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
4 X/ |+ V9 |* b. e2 U7 a% QMultinomial Logistic Regression , 多项逻辑斯蒂回归7 o2 k. m" d* k
Multiple comparison, 多重比较' @ L( G- Y. V9 O/ H+ [
Multiple correlation , 复相关
}2 o# K! ~. \Multiple covariance, 多元协方差
" @' V, U0 m# J7 d0 g" k, sMultiple linear regression, 多元线性回归
) N4 h) {8 W- z' i7 r6 g% QMultiple response , 多重选项
' K" C8 f4 H3 V3 J2 g! S' \Multiple solutions, 多解) e$ V8 X% G/ c# m
Multiplication theorem, 乘法定理
2 @. T0 m! ~. N1 H7 L* m' z+ V% sMultiresponse, 多元响应' [% p: P% V; c2 I" s3 X- u) i
Multi-stage sampling, 多阶段抽样+ Z. ^! V* `3 V- Q, h" j$ e
Multivariate T distribution, 多元T分布& A% f& D/ }' k& P/ @ o) X7 g
Mutual exclusive, 互不相容5 c- Q+ v* G1 \$ _0 @6 E9 e. ?
Mutual independence, 互相独立 v* r7 g6 `" y6 F
Natural boundary, 自然边界# C& f* u' o) z W6 ^. Z
Natural dead, 自然死亡
' e% |/ J/ u# q: @( J) v Z ]' sNatural zero, 自然零3 a2 [6 |5 ^5 X) F5 Z M$ {
Negative correlation, 负相关 X5 t9 c5 [0 L1 A2 m2 J* G
Negative linear correlation, 负线性相关8 F) B- S6 p9 f! G$ k& T
Negatively skewed, 负偏! X3 C0 n/ [6 c3 b2 V( r* n
Newman-Keuls method, q检验% W3 [% C7 v( ^3 @. s
NK method, q检验8 Y6 B2 V, {$ f- [' I) M. I% Q. w
No statistical significance, 无统计意义 z e( B. v& c7 z. Z6 u1 l# G
Nominal variable, 名义变量
9 @, B' Y5 H/ S- ?; v) `Nonconstancy of variability, 变异的非定常性* n. D% D( v E. v1 F5 H
Nonlinear regression, 非线性相关0 k3 A" q+ g9 n t5 T* c( O
Nonparametric statistics, 非参数统计9 `" U- a3 r3 s: o" H
Nonparametric test, 非参数检验4 C1 C& E+ _' k- i6 e" J
Nonparametric tests, 非参数检验: C/ Z4 Z& u0 f- J
Normal deviate, 正态离差
1 l6 H) E5 a7 c+ U7 x. vNormal distribution, 正态分布* N, k! y& J b/ n( I4 X0 \
Normal equation, 正规方程组& V# J# {) c' X2 j3 ^4 R
Normal ranges, 正常范围% ~) m0 {& o2 A
Normal value, 正常值
% D3 ?* h* t# M' Y) ]- T, ~2 R! i- ?Nuisance parameter, 多余参数/讨厌参数
) V( ^1 @' e. y5 jNull hypothesis, 无效假设
. p0 a: q2 ?6 u6 e+ Y6 _. G- {Numerical variable, 数值变量8 v* \8 w* E# [3 @5 n: d
Objective function, 目标函数. f- V% J7 Q2 b7 q
Observation unit, 观察单位) h7 K3 _& g& I# {! H7 x
Observed value, 观察值
% ?) {. g7 R0 J# c8 h8 T" G' d2 W" mOne sided test, 单侧检验6 q2 g' y/ A, _+ E
One-way analysis of variance, 单因素方差分析( G, f3 r4 O/ l
Oneway ANOVA , 单因素方差分析% T+ l7 J3 y* ~
Open sequential trial, 开放型序贯设计+ F8 Q. B+ J5 e/ L& p& G9 T
Optrim, 优切尾
% P. L8 B# Q$ NOptrim efficiency, 优切尾效率) p! s" h/ t& Y. j* V& L
Order statistics, 顺序统计量" k- p1 L) a- d4 x7 v$ g2 Z3 ]
Ordered categories, 有序分类
0 q: }! P) q8 B8 o6 C. BOrdinal logistic regression , 序数逻辑斯蒂回归5 P& K3 b# p$ c3 d- S3 R9 z
Ordinal variable, 有序变量
" c7 s o1 f/ c/ h- }: o. @Orthogonal basis, 正交基, `1 q! V, w' F+ a5 c
Orthogonal design, 正交试验设计 x3 r9 |) Z h+ p$ [
Orthogonality conditions, 正交条件 D2 Z6 p0 K) T% l, G/ K
ORTHOPLAN, 正交设计
+ ]& ^) B. z2 WOutlier cutoffs, 离群值截断点
% h# D5 V4 a2 bOutliers, 极端值
$ v+ @+ @7 Y$ E. m% IOVERALS , 多组变量的非线性正规相关 7 l( C" f5 A0 z9 I7 o) X
Overshoot, 迭代过度
J: e' ~2 h8 ?Paired design, 配对设计 M& ~+ g( i, J) f A l
Paired sample, 配对样本
3 p7 u- x# [ g6 [& DPairwise slopes, 成对斜率3 z( s0 }& N; g$ R0 O# b' Q2 i
Parabola, 抛物线; k/ q) ]7 o2 Z" D. Z% f
Parallel tests, 平行试验
) p* U4 }) }9 o1 u3 K2 dParameter, 参数' T) j+ p# L6 v7 X! p3 D
Parametric statistics, 参数统计
8 h9 e6 a3 W) O' |Parametric test, 参数检验
I- s0 T% Z5 L% C+ C+ e4 aPartial correlation, 偏相关
$ G' F l. ]6 I8 r# S6 v9 WPartial regression, 偏回归
4 X/ B- A- T$ c% sPartial sorting, 偏排序# n5 i2 w7 Z3 M2 o0 {- {
Partials residuals, 偏残差
8 V' a+ K( F, a. wPattern, 模式+ S+ }4 q; A; I1 e: P7 [) k
Pearson curves, 皮尔逊曲线; \( z/ Z, U; j" ~/ {; x1 @$ v
Peeling, 退层# I/ ^1 T4 J- _$ P! d) q$ y% U8 l. T
Percent bar graph, 百分条形图
! F' L' X- `) L2 ~+ MPercentage, 百分比0 l6 c @! W, J& Z5 c% y
Percentile, 百分位数
1 E. W X# T8 ~" A! F* z" H% ~Percentile curves, 百分位曲线
/ E9 J. z/ j- f: X* ePeriodicity, 周期性
& N& R6 `9 B# O0 p- O* O7 ~/ zPermutation, 排列7 |; e! z+ J# U% J2 }
P-estimator, P估计量
% d0 n- ~8 P( b7 }& UPie graph, 饼图) ]: h1 u. P1 M
Pitman estimator, 皮特曼估计量
6 N. \- X. ] B% _8 n$ wPivot, 枢轴量9 e1 _/ N' l# \7 h9 H
Planar, 平坦4 x; K- y% w0 o. \
Planar assumption, 平面的假设, q" N. a9 K9 p7 K+ S) Q3 y
PLANCARDS, 生成试验的计划卡% x& W6 m/ @* _& b x, m! h) M
Point estimation, 点估计/ B/ b6 l8 q8 d( Q9 s- J
Poisson distribution, 泊松分布- B. [% d3 P1 Z! W$ P
Polishing, 平滑
; K0 ]5 r* F% W! S& j# p; ~( n* IPolled standard deviation, 合并标准差" a- a+ H* n2 G/ m0 o- _
Polled variance, 合并方差
1 x: C& A& z& y5 SPolygon, 多边图
P9 B% o2 h' w: ^9 oPolynomial, 多项式- H/ o% _: A' ]: M
Polynomial curve, 多项式曲线1 D D; c* j# g) u. o+ ]# K- R
Population, 总体' n) y! C; |1 A3 B) } d
Population attributable risk, 人群归因危险度
0 r$ H1 R, F6 @1 APositive correlation, 正相关
, B1 H. Y) \/ t5 m6 YPositively skewed, 正偏
& Z: k' a% G& ?7 {+ t {Posterior distribution, 后验分布& `* Z# S, n6 a3 }
Power of a test, 检验效能
: e6 L( p, L$ w# oPrecision, 精密度
0 M6 {& E, l0 |+ fPredicted value, 预测值- ^% Q5 G2 H) S' n/ ^3 T* ?
Preliminary analysis, 预备性分析
( }1 O6 |" S0 J/ R$ M7 Y6 XPrincipal component analysis, 主成分分析1 O2 I5 O! u/ L! p
Prior distribution, 先验分布
9 N7 [4 U3 x, |0 aPrior probability, 先验概率& w# B* P. A) M) U: k% z: m6 E+ j
Probabilistic model, 概率模型2 `( Z/ r- m) ^
probability, 概率
" A l/ L7 S7 n) D) {8 ?% n zProbability density, 概率密度
2 e8 X- B# o, R. G7 @5 hProduct moment, 乘积矩/协方差8 f! o7 X" j* ^4 G7 F$ Y
Profile trace, 截面迹图& i$ c' j I+ i
Proportion, 比/构成比, _0 I @$ W! y" B1 v3 X: @$ X! S
Proportion allocation in stratified random sampling, 按比例分层随机抽样
3 x1 v4 I( m0 o. F: I$ ]7 AProportionate, 成比例
- R8 @0 a5 o! w8 FProportionate sub-class numbers, 成比例次级组含量
3 w/ {' L( |, \8 j& zProspective study, 前瞻性调查# g. l' p4 }0 A8 ^: {; T; z1 u
Proximities, 亲近性
: ~( w! H2 [4 DPseudo F test, 近似F检验) I4 X* h7 ` ~, X: ~3 @( [" a- j% c" E
Pseudo model, 近似模型5 U& w6 x, U2 G7 J! N
Pseudosigma, 伪标准差
! {6 j* s+ `* HPurposive sampling, 有目的抽样( A" E, U- d9 _% d+ a7 w0 ?, r1 Q
QR decomposition, QR分解% \- |+ K" L7 ?/ @0 }4 |: s
Quadratic approximation, 二次近似; s- t) S* V$ t2 K8 v. T
Qualitative classification, 属性分类+ w7 c. G8 A: n' k& Y- M
Qualitative method, 定性方法0 C/ g/ r" [- i# p6 b$ h
Quantile-quantile plot, 分位数-分位数图/Q-Q图6 p$ s6 q7 [& ]/ R" w1 C# w
Quantitative analysis, 定量分析
$ V7 o. h% F3 D! y5 T; e0 o BQuartile, 四分位数$ V) E6 u2 Y2 r1 y5 [8 ~
Quick Cluster, 快速聚类/ V3 v! x; q* p4 \" g. M5 ~
Radix sort, 基数排序: l, z/ p7 u4 a* n+ m; U# P
Random allocation, 随机化分组
( V+ s' m0 N0 x. y% z; c, S% _Random blocks design, 随机区组设计
5 P2 n. F9 Z0 [4 f5 p: S3 RRandom event, 随机事件
/ F: l' { h& v* y" {2 I$ @% pRandomization, 随机化0 r3 L9 r% K$ ~- B% X! _1 ]
Range, 极差/全距
3 T5 U. {6 v' E! h# p2 p* cRank correlation, 等级相关; Q# e. W( M5 X1 o- `
Rank sum test, 秩和检验+ X% w+ V6 f5 q
Rank test, 秩检验; U& q2 h0 w! X+ X2 [4 X+ q
Ranked data, 等级资料
: \4 v" E3 K$ C R5 w1 j; L* DRate, 比率
! w) J% o/ t2 K" Y& k5 xRatio, 比例
6 }2 h' s) V' Y1 P' bRaw data, 原始资料 j) L% K8 g) ^! ^& A
Raw residual, 原始残差
' r- ]1 N3 @: dRayleigh's test, 雷氏检验9 h: f P' S8 E4 l( y
Rayleigh's Z, 雷氏Z值
# y% ~. I$ d6 B" mReciprocal, 倒数
y% M+ o7 t0 R X, BReciprocal transformation, 倒数变换3 n+ j V( ~. T* J, i
Recording, 记录( \; L2 ?% F' w7 `8 A2 s" P8 c6 {
Redescending estimators, 回降估计量
, h. T8 S/ A2 f8 KReducing dimensions, 降维
' h# \, g6 d1 uRe-expression, 重新表达
0 w/ I# _$ j( oReference set, 标准组) ^0 T& I' B+ f% n
Region of acceptance, 接受域
$ @! P) K6 O7 q; W2 H& @& ^Regression coefficient, 回归系数8 k. }/ E, H/ \) v
Regression sum of square, 回归平方和5 W4 l% A c& }/ Y7 z) L
Rejection point, 拒绝点5 l) V8 ~6 D9 w+ Z c. {- n7 P- a
Relative dispersion, 相对离散度+ y/ t& z; p5 g7 i- {' p0 L
Relative number, 相对数
7 _ C: x# W Q h% IReliability, 可靠性" m8 q+ }- | i) e% H( Y9 }7 L$ B- Z, O
Reparametrization, 重新设置参数
4 ]2 G: @% ]0 U8 I8 a f2 gReplication, 重复8 ]* _ w9 M+ o+ o! b' k3 r6 c
Report Summaries, 报告摘要) C+ k. L, Z5 M0 R# t* D
Residual sum of square, 剩余平方和
& U2 G1 P* T h2 y" D3 R* vResistance, 耐抗性& B, c! j) n7 B- [4 `# v7 D
Resistant line, 耐抗线& x. M7 y* G* `2 l- O6 O5 } a+ x
Resistant technique, 耐抗技术# v. a+ [: L) ~' `6 Y- a
R-estimator of location, 位置R估计量3 I3 o% N* e* K" A
R-estimator of scale, 尺度R估计量6 H h: W( O* D5 F# [: p
Retrospective study, 回顾性调查. r } t/ d* q K8 ]
Ridge trace, 岭迹
6 Z! O0 u" Q3 t4 [+ `Ridit analysis, Ridit分析
' A; d2 O0 _* A+ K4 n" i' f ORotation, 旋转: ~7 {9 X# q. n1 X" W
Rounding, 舍入% O% i6 I7 L, x* e" M
Row, 行9 l8 k; Y3 u0 q$ y+ t5 Z# v
Row effects, 行效应0 U* x4 b( X/ C/ }) G: j
Row factor, 行因素
0 t0 [1 l) U# U/ z6 RRXC table, RXC表
( m$ N0 U& g& [, ^Sample, 样本
4 b3 b. J: w. m* e3 _# x( l7 HSample regression coefficient, 样本回归系数) w/ e1 _: q+ w! m
Sample size, 样本量
; b3 y" U) N, d) P! cSample standard deviation, 样本标准差, J+ b6 v) D7 n' n) N6 B/ z7 R
Sampling error, 抽样误差
1 c3 Z9 h; `- d# S% Y4 s) _SAS(Statistical analysis system ), SAS统计软件包8 T7 q$ }# Y6 n/ @0 V b. V, T
Scale, 尺度/量表
. I( B1 M' k* N- M! VScatter diagram, 散点图
& F$ }3 w5 B: p- b, \Schematic plot, 示意图/简图 T5 U$ N9 w( Z# G) u" r
Score test, 计分检验$ l& y# q4 Z( j5 p2 y Q
Screening, 筛检
, Y' ?( e, S$ u& B, aSEASON, 季节分析
* v- |8 x- Q2 V& A( p/ c9 jSecond derivative, 二阶导数4 V1 ?" z0 C1 r O: }: y
Second principal component, 第二主成分0 d3 p+ a# t" R6 X: W8 z* q
SEM (Structural equation modeling), 结构化方程模型
, g+ `" G9 [3 e1 iSemi-logarithmic graph, 半对数图5 \2 Z/ k3 O' E r T
Semi-logarithmic paper, 半对数格纸
' H# m% u! g) Q9 e, S" cSensitivity curve, 敏感度曲线( g( V' ?1 W" n: ?0 D& n/ U, a
Sequential analysis, 贯序分析
: T2 U- c$ T, x) ESequential data set, 顺序数据集% Z" \1 ^0 J: C: l" S* i% R
Sequential design, 贯序设计
3 [4 P5 w6 X% KSequential method, 贯序法
) B* Y2 S y; t- j/ g/ b" hSequential test, 贯序检验法, \% u: D. Q! Q% J
Serial tests, 系列试验* w0 }7 M1 J }4 Q. T
Short-cut method, 简捷法
: j0 u; Z) p, d3 X4 I6 V& ySigmoid curve, S形曲线
& c7 |# ]% _9 G& pSign function, 正负号函数3 U# c# [6 {" n. B- X% Z8 T
Sign test, 符号检验, X9 @& E' P: R
Signed rank, 符号秩% j6 C5 G, v' M# E' S! Y
Significance test, 显著性检验
$ c" T: R8 [0 u9 B8 B, I3 aSignificant figure, 有效数字
* U6 B: Q2 I4 o; |; b+ ^Simple cluster sampling, 简单整群抽样
% _# d# k6 N$ D- s* d0 o6 BSimple correlation, 简单相关/ L' _1 R) k+ m, A% a3 ^4 I
Simple random sampling, 简单随机抽样
( |1 L7 O1 L! xSimple regression, 简单回归! K# x, j" j4 \" ?1 V7 J6 W7 r ]5 r
simple table, 简单表
, B+ H0 h' R' W9 @, SSine estimator, 正弦估计量
5 i3 A- ?7 b8 [/ r( PSingle-valued estimate, 单值估计6 i: f+ \# n9 u- n) E. e1 L% d N
Singular matrix, 奇异矩阵
' k% X5 i E |8 C; u6 ]Skewed distribution, 偏斜分布0 Q. w( }; m& c7 ?: m$ ]
Skewness, 偏度
0 T% _) C/ W1 b' V$ ZSlash distribution, 斜线分布
) R5 W# L/ ^/ n" i H+ K* e0 q1 S. ~Slope, 斜率5 `) p9 j6 E' C6 n; b
Smirnov test, 斯米尔诺夫检验, A4 H' w0 ^; A6 m$ v4 K
Source of variation, 变异来源
/ r& J/ e& } S2 Z/ t+ ESpearman rank correlation, 斯皮尔曼等级相关
3 B/ e2 v9 n5 YSpecific factor, 特殊因子/ J2 k, e4 m1 z; f0 I1 f. e
Specific factor variance, 特殊因子方差
; D$ y) z# O" V. G+ Z& ~! ~" \Spectra , 频谱$ a% Q0 C7 k. v$ z0 S
Spherical distribution, 球型正态分布1 u; D0 E5 T) ~3 U; c# @
Spread, 展布
4 }% c* j# @" j- NSPSS(Statistical package for the social science), SPSS统计软件包
3 x; `+ X0 ~# H9 E0 u/ B! P2 cSpurious correlation, 假性相关
+ a# q) P- H0 z* d" ]Square root transformation, 平方根变换
. _1 e; g) D: c. e; m. Q. CStabilizing variance, 稳定方差
: F! y+ y0 v& `* ]2 {Standard deviation, 标准差
& Y( A/ T4 I; l* c3 PStandard error, 标准误. ]7 k4 l( _( O$ a
Standard error of difference, 差别的标准误6 }/ C1 I8 M) x
Standard error of estimate, 标准估计误差
+ _) E' R& B2 o& OStandard error of rate, 率的标准误
" O6 a" P6 x8 H8 S/ s' ZStandard normal distribution, 标准正态分布( h' ~1 s% F$ t+ { w% j( _
Standardization, 标准化
6 I. @8 R7 @% w8 x0 |Starting value, 起始值9 y6 p F3 ^! L& s
Statistic, 统计量5 Y& z5 \/ u. }+ k1 h
Statistical control, 统计控制
$ E# [8 ]& F7 P. G8 |' xStatistical graph, 统计图0 N* r: C" f) }
Statistical inference, 统计推断: y5 z4 u8 y5 V- A9 l. u9 c
Statistical table, 统计表
! a& B% S! ?% p8 W* kSteepest descent, 最速下降法: m6 p2 {3 `% i
Stem and leaf display, 茎叶图
* R# k5 k, i; C+ kStep factor, 步长因子
2 V5 e r3 w3 w. h% ^Stepwise regression, 逐步回归
6 v; L2 u- B) g9 Z5 wStorage, 存/ Q( P9 R& h! \8 A/ V, F" s
Strata, 层（复数）
6 l' v- B& F, i8 ZStratified sampling, 分层抽样/ z U5 }5 P6 Z/ M' u
Stratified sampling, 分层抽样
# q3 _0 d5 M4 s2 t+ u9 i: `Strength, 强度" b6 Z5 g+ g$ Y4 A4 b: U
Stringency, 严密性
* `1 s. k) E1 T- w6 f& BStructural relationship, 结构关系
3 Y: \% ^3 l9 K1 j; o; tStudentized residual, 学生化残差/t化残差# h0 S" f, l* ]
Sub-class numbers, 次级组含量
" X9 H; Z# O+ u$ c% ~Subdividing, 分割 [# M/ k P* |# x
Sufficient statistic, 充分统计量/ J, H9 r [8 m: s
Sum of products, 积和5 c% x: ?( L) l0 T' G/ g9 |6 j
Sum of squares, 离差平方和. ^' P" q* h% X' i
Sum of squares about regression, 回归平方和
" |5 N3 s4 t9 }9 q) a' ~Sum of squares between groups, 组间平方和
& G& E% a w \Sum of squares of partial regression, 偏回归平方和* }. d& M0 o7 c
Sure event, 必然事件( l4 }1 n" \: b+ t5 S4 f+ L
Survey, 调查
0 }2 _* x. _) P* X; G. ISurvival, 生存分析
1 Q& t: ?! l$ [1 o g9 rSurvival rate, 生存率
: M; ]9 F) Y$ ^% z# iSuspended root gram, 悬吊根图
: { _$ F# f7 h1 f; I" {; s& ?6 E5 mSymmetry, 对称& s& @: ?. P9 a4 N# z, g
Systematic error, 系统误差
( l) f9 z5 G- ]' aSystematic sampling, 系统抽样
' q( v, {* E6 \$ hTags, 标签4 R Z; {1 _3 U7 V
Tail area, 尾部面积+ N# q7 o& W, e0 q
Tail length, 尾长
8 P% ?! n( I0 R& f7 wTail weight, 尾重
: ?9 v$ h% Y A1 KTangent line, 切线
% A% p7 @& T( {8 rTarget distribution, 目标分布
* d) H# w8 P1 vTaylor series, 泰勒级数
7 a X: @: I7 c% d6 OTendency of dispersion, 离散趋势
8 K& ?' H! p+ ~; [& N+ p- K1 mTesting of hypotheses, 假设检验
8 s1 u6 @- \/ ~0 \% f- PTheoretical frequency, 理论频数
' I8 x/ M% S7 D- H0 rTime series, 时间序列6 y" @$ w9 r4 d
Tolerance interval, 容忍区间
. D5 _& \" s5 @# ~6 sTolerance lower limit, 容忍下限
; W9 F4 |8 n2 }4 F' o) S" f9 sTolerance upper limit, 容忍上限& @! L4 O" @6 i
Torsion, 扰率6 w9 ~3 l5 W I4 z* g3 Z `8 e
Total sum of square, 总平方和
; @; P: L* X" ^6 h1 qTotal variation, 总变异
+ m4 x5 E6 @5 q: ATransformation, 转换
+ n# O9 G6 n; p1 c7 TTreatment, 处理
% f+ U B7 P. J F( _8 I gTrend, 趋势9 X4 L9 L3 @/ j( t0 z
Trend of percentage, 百分比趋势, ]& A$ [9 d5 e4 i
Trial, 试验% s* W3 ^2 `0 q+ @
Trial and error method, 试错法) l4 Y' a7 I2 Y7 W% M7 n+ k
Tuning constant, 细调常数
% ]: i2 y3 t$ U( dTwo sided test, 双向检验
& ~4 c6 D2 l! M9 L; h* t6 D% e" x: w" g6 yTwo-stage least squares, 二阶最小平方 h3 X8 V* v, O+ n9 f/ P
Two-stage sampling, 二阶段抽样
" Y, {' m6 V- Q5 F! PTwo-tailed test, 双侧检验
* i0 j2 U; U ]. a% W: @( a/ s& MTwo-way analysis of variance, 双因素方差分析2 n# k5 t8 D7 y( G( G( J* t
Two-way table, 双向表
* @1 `5 Y, v1 |7 { uType I error, 一类错误/α错误) v, w9 A! w6 g
Type II error, 二类错误/β错误4 c& P& z6 H6 j% H9 y1 t
UMVU, 方差一致最小无偏估计简称7 F$ _9 x, r. t
Unbiased estimate, 无偏估计
% S+ l4 A! H+ J# v+ @2 ?+ HUnconstrained nonlinear regression , 无约束非线性回归4 @3 D: ~& g; \* V4 F
Unequal subclass number, 不等次级组含量- H/ \+ j* I8 _7 K! g
Ungrouped data, 不分组资料
( T& X$ d) _* c- qUniform coordinate, 均匀坐标* l K2 A$ ^1 U( y( {7 {- j/ d
Uniform distribution, 均匀分布
- j$ E6 _, C! a0 F& E& O) LUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
8 ^6 d) Q! }/ g6 L0 Z2 sUnit, 单元5 d* M! d1 j0 v8 s
Unordered categories, 无序分类
8 h6 z4 _! `. f/ |Upper limit, 上限
: V. G5 C3 T! T3 P) FUpward rank, 升秩 v3 W6 K2 L! k
Vague concept, 模糊概念
3 |- G. I& ?% |7 ^& G* R% eValidity, 有效性
: R( J' z/ z3 B) S) \% uVARCOMP (Variance component estimation), 方差元素估计. ]* A3 f k" Y: H
Variability, 变异性
) L; t/ t$ ~ r. L1 ?) m; t, U+ j3 \Variable, 变量" Y% X* j' u7 c8 g2 k+ e1 l
Variance, 方差
4 n0 o( Z, c& N) ^4 L) rVariation, 变异! n7 ?- m* @' K7 M
Varimax orthogonal rotation, 方差最大正交旋转% L3 Q z i3 t# I0 G
Volume of distribution, 容积2 T" Z/ N6 v& K& S0 ?& J
W test, W检验
8 W; u4 M( Z" R- e8 E1 i' mWeibull distribution, 威布尔分布) p; u1 y1 ^, }* @ ^; \$ G4 v
Weight, 权数
: k! a, c8 D$ u* I$ X$ FWeighted Chi-square test, 加权卡方检验/Cochran检验
% z/ I6 w- k6 ZWeighted linear regression method, 加权直线回归! f7 C4 w& u9 p( D, D- K. m
Weighted mean, 加权平均数0 Y8 M g" Q- D! O! D
Weighted mean square, 加权平均方差
) c# {7 {& ]6 }4 B* l: ~+ z3 YWeighted sum of square, 加权平方和3 C/ f+ M$ |5 v
Weighting coefficient, 权重系数
% z' H \0 ~* [Weighting method, 加权法 1 N. F0 E' E$ S# n0 d/ z& Q# p2 x/ @
W-estimation, W估计量
7 E& V8 e/ m( j6 D( L8 `- jW-estimation of location, 位置W估计量- Y2 ^" g- A1 E! F9 K
Width, 宽度* p9 g. Q8 p3 e3 |3 o0 h
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验% \) l" w" q! F) y, m j
Wild point, 野点/狂点- E9 m2 M: k, o9 o" f5 h
Wild value, 野值/狂值
) }% l' E. G7 i% B7 H3 }9 aWinsorized mean, 缩尾均值
) U; D+ Z. ^, B s& AWithdraw, 失访
' R$ w* t7 `4 o# VYouden's index, 尤登指数- p/ r3 w% v/ |: u6 h' l. z5 @+ M$ D
Z test, Z检验
2 f6 ?1 r$ G( {, pZero correlation, 零相关. s% e9 v4 }- ^
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
